An essential stage in computer aided diagnosis of chest X rays is automated lung segmentation. Due to rib cages and the unique modalities of each persons lungs, it is essential to construct an effective automated lung segmentation model. This paper presents a reliable model for the segmentation of lungs in chest radiographs. Our model overcomes the challenges by learning to ignore unimportant areas in the source Chest Radiograph and emphasize important features for lung segmentation. We evaluate our model on public datasets, Montgomery and Shenzhen. The proposed model has a DICE coefficient of 98.1 percent which demonstrates the reliability of our model.

翻译：计算机辅助诊断胸部X射线的一个重要阶段是自动肺断裂。由于肋骨笼子和每个人肺的独特模式,必须建立一个有效的自动肺断裂模型。本文为胸部射电图中肺部分割提供了一个可靠的模型。我们的模型通过学会忽略源头胸透射线中不重要的领域和强调肺切裂的重要特征克服了挑战。我们评估了公共数据集模型蒙哥马利和深圳。拟议的模型具有98.1%的DICE系数,显示了模型的可靠性。